Environmental and Economic Research and Development Program

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1 Public Service Commission of Wisconsin & the Statewide Energy Efficiency and Renewables Administration Environmental and Economic Research and Development Program Final Report March 2011 Energy Intensity and Environmental Impact of integrated Dairy and Bio-Energy Systems in Wisconsin Prepared by: Douglas Reinemann, Thais Passos-Fonseca, Horacio Aguirre- Villegas, Simone Kraatz, University of Wisconsin-Madison, Biological Systems Engineering; Franco Milani, Food Science and Center for Dairy Research; Louis Armentano, Victor Cabrera and Michel Wattiaux, Dairy Science; John Norman: Soil Science This report was funded through the Wisconsin FOCUS ON ENERGY Program. i

2 ENERGY INTENSITY AND ENVIRONMENTAL IMPACT OF INTEGRATED DAIRY AND BIO-ENERGY SYSTEMSS IN WISCONSINN 2/1/2011 THE GREEN CHEESE PROJECT The University of Wisconsin Green Cheesee Team: Douglas Reinemann, Thais Passos-Fonseca, Horacio Aguirre-Villegas, Simone Kraatz: Biological Systems Engineering Franco Milani: Food Science and Center for Dairy Research Louis Armentano, Victor Cabrera, Michel Wattiaux: Dairy Science John Norman: Soil Science ii

3 Contents INTRODUCTION... 1 GREENHOUSE GAS EMISSIONS AND ENERGY INTENSITY IN THE DAIRY SECTOR... 2 DAIRYLAND WISCONSIN... 3 Greenhouse gas (GHG) emissions from Wisconsin s dairy sector... 4 Integration of dairy & bio-fuels in Wisconsin... 4 LIFE CYCLE ASSESSMENT (LCA)... 5 LCA terms and definitions... 6 THE GREEN CHEESE PROJECT... 7 Green Cheese Objectives... 7 Green Cheese Methods... 8 Life Cycle Inventory Data... 8 Impact Assessment... 8 Milk Production at the Farm-Gate... 9 Milk Processing and Cheese-making RESULTS AND INTERPRETATION Milk Production Net Energy Intensity GHG Emissions Land use Results from the Dairy Plant phase Dairy Farm gate to Dairy Plant gate Cradle to Dairy Plant gate CALCULATIONS FOR THE STATE OF WISCONSIN From cradle to farm gate From farm gate to plant gate PRACTICES TO REDUCE ENVIRONMENTAL IMPACTS OF DAIRY PRODUCTION Co-products from corn ethanol production (dry distillers grains with solubles DDGS) Milk yield Manure management Anaerobic digesters Utilization of biogas as a fuel CONTINUING WORK iii

4 List of Figures Figure 1. Life cycle assesssment boundaries for cheese production, from cradle to plant gate Figure 2. Estimated GHG emissions for milk production, from cradle to farm gate, from different studies. The term "accounting for biofuels" means that milk production that uses co-products of biofuels benefits from GHG credits from biofuels industry Figure 3. types of cheese produced in wisconsin in 2009 (USDA 2009 Dairy Products Annual Summary) Figure 4. LCA Stages (ISO 14040) Figure 5. the Main processes of the production of Cheddar cheese and the related impact categories FIGURE 6. System boundaries of the milk production phase FIGURE 7. System boundaries of the dairy plant phase Figure 8. Allocation based on physical processes and total solids in cheese production Figure 9. Net energy intensity of milk production for selected diets, with different accounting criteria. Negative values of net energy intensity indicate net positive energy output from the system accounting for the energy content of the bio-fuels produced or for the avoided energy to produce fossil fuels Figure 10. Direct energy is the energy used on the farm in forms of electricity and fuels. Indirect energy is the energy used to produce the fertilizers, seeds, herbicides, pesticides, lime, liquid fuels, electricity, natural gas, and machinery used for farming Figure 11. Comparison among five dairy diets in best management practices (in the Green Cheese model) and the DMI study on Region 3 (which includes Wisconsin) shows that the 2 major areas in which there is room for improvement are: manure management and crop production systems Figure 12 GHG emissions from milk production for selected diets, according to distinct accounting criteria Figure 13 GHG emissions and net energy intensity of milk production up to farm gate. The effect of anaerobic digesters is mild when biogas is not used as a fuel replacing natural gas, and larger when it is used as a fuel, especially in terms of net energy intensity. Negative values of net energy intensity indicate net positive energy output from the system accounting for the energy content of the bio-fuels produced or for the avoided energy to produce fossil fuels Figure 14. Land use, GHG emissions, and net energy intensity of milk production for selected diets, accounting for bio-fuels. All values presented in relation to Diet CADS (100%). The two bars at the right show the net energy intensity without and with biogas. Negative values of net energy intensity indicate net positive energy output from the system accounting for the energy content of the bio-fuels produced or for the avoided energy to produce fossil fuels Figure 15. Energy intensity of cheese production when only cheese is produced Figure 16. Energy intensity of cheese production when cheese, dry whey, and whey cream are produced Figure 17. Comparison of energy intensity of Scenario 1 (only cheese is produced) to Scenario 2 (cheese and whey are produced) Figure 18. GHG emissions when only cheese is produced Figure 19 GHG emissions when cheese, dry whey, and whey cream are produced Figure 20 Comparison of GHG emissions for Scenario 1 (only cheese is produced) and Scenario 2 (cheese and whey are produced) Figure 21. Net Energy of aggregated annual cheese production in Wisconsin, for selected scenarios31 iv

5 Figure 22. GHG emissions from aggregated annual cheese production in Wisconsin, for selected scenarios Figure 23 Effect of milk yield on the energy intensity and GHG emissions from milk production Figure 24 Anaerobic digester - Crave Brothers Farm, Waterloo, Wisconsin v

6 T HE GREEN CHEEE SE PROJ ECT INTRODUCTION Energy Intensity and Environmental Impact of integrated Dairy and Bio-Energy Systems in Wisconsin The environmental impact of production technologies and management decisions in food systems has become more important as the challenges of climate change increase and availability of natural resources decrease. There are a number of well known green or environmentally friendly management practices that can reduce the undesirable environmental consequences of milk production including: optimizing dairy diets, wisely managing waste, adopting optimal cropping patterns and conservative field operations, improving energy efficiency of food production and generating energy on farms. The Green Cheese study is a group effort focused on identifying synergies that reduce Green-House Gas (GHG) emissions, the use of fossil fuels, and other environmental impacts of integrated dairy and bio-fuels production systems in Wisconsin (Figure 1). A Life Cycle Assessment (LCA) of these practices has been done by the Green Cheese Team at the University of Wisconsin to assess these objectives. FIGURE 1. LIFE CYCLE ASSESSSMENT BOUNDARIES FOR CHEESE PRODUCTION, FROM CRADLE TO PLANT GATE. 1

7 GREENHOUSE GAS EMISSIONS AND ENERGY INTENSITY IN THE DAIRY SECTOR A recent study by the Food and Agriculture Organization (FAO) estimated that the world s dairy sector contributes 4.0% (+-26%) to the total global anthropogenic greenhouse gas (GHG) emissions, including emissions associated with milk production, milk processing and transportation, and emissions from meat production from dairy-related enterprises. This same study reported that GHG emissions from milk production at the farm gate range from 1.3 to 7.5 kg CO2-eq per kg of fat and protein-corrected milk, depending on the farming system and region (FAO, 2010) (Figure 2). An analysis of 60 studies by the International Dairy Federation (IDF) concluded that about 80% of the GHG emissions from producing dairy products originate from on-farm sources; mainly emissions from soils (crop production), cows, and manure. The GHG emissionss reported in the IDF study ranged from 0.40 to kg CO2-eq/kg milk, and the energy intensity ranged from 1.31 to 6.57 MJ/kg milk (IDF, 2009) (Figure 2). A study by the University of Arkansas on the Carbon Footprint of Fluid Milk reported an average of 1.22 kg CO2-eq/kg of milk at the farm gate for the US, ranging from 1.04 to 1.47, depending of the region. In this study, the average for the states of Minnesota, Iowa, Missouri, Wisconsin, Illinois, Indiana, Michigan, and Ohio ( Region 3) was 1.1 kg CO2-eq/kg of milk at the farm gate (DMI, 2010). This Green Cheese study for Wisconsin ranged from to 0.89 kg CO2-eq/kg of milk at the farm gate, depending on the dairy diet and manure handling methods (Figure 2). FIGURE 2. ESTIMATED GHG EMISSIONS FOR MILK PRODUCTION, FROM CRADLE TO FARM GATE, FROM DIFFERENT STUDIES. THE TERM "ACCOUNTING FOR BIOFUELS" MEANS THAT MILK PRODUCTION THAT USES CO-PRODUCTS OF BIOFUELS BENEFITS FROM GHG CREDITS FROM BIOFUELS INDUSTRY. Most of the differences across these studies are accounted for by differences in management practices across geographic regions. The largest single contributor to GHG emissions is enteric methane (CH 4 ) produced during rumination of dairy cows (about 52% of the total emissions), the second largest contributor is N 2 O emitted from soils producing dairy feeds (between 27 and 38% of the total emissions), and the third largest is CO 2 emitted from cows rumens and from manure (between 10 and 21% of the total emissions) (FAO, 2010). 2

8 Scientific studies that have resulted in varying estimates of GHGG emissions from milk production whichh are influenced by a number of factors including; milk yield per cow, differing dairy diets, and different manure management practices. Several studiess have evaluated adjustments in dairy diet compositions to reduce enteric methane emissions from cows. Others have investigated reduction of methane emission from slurry manure through manure management practices. From the dairy farm perspective, methods of reducing GHG emissions can be technically and economically challenging. One challenge to Wisconsin dairy producers are regulations that limit the amount of phosphorous applied to fields which can limit manure application. The balance of crop nutrients may need to be supplied by the use of synthetic nitrogen fertilizers to supply feed crop demands. DAIRYLAND WISCONSIN According to the USDA (NASS, 2010), Wisconsin ranks as the second largest state for both the number of dairy cows and amount of milk produced. Dairy production is one of the most important economic activities in Wisconsin with approximately 1.26 million milking cows produced more than 25,239 million pounds of milk in 2009 (USDA, 2011). According to the Wisconsin Milk Marketing Board dairy activity generates nearly US$ 26.5 billion each year to the State s economy. Wisconsin contributed 26% of the total US milk production of 10.1 billion pounds in 2009, and Wisconsin is the leading cheese producer in the U.S. with mozzarellaa and cheddar the most produced varieties (Figure 3). FIGURE 3. TYPES OF CHEESE PRODUCED IN WISCONSIN IN 2009 (USDA 2009 DAIRY PRODUCTS ANNUAL SUMMARY). 3

9 Greenhouse gas (GHG) emissions from Wisconsin s dairy sector In 2003, greenhouse gas (GHG) emissions from Wisconsin s agricultural sector were estimated to represent 9% of the statewide GHG emissions. Much of Wisconsin s agricultural emissions were in the form of CH 4 from animal digestive processes associated with the dairy industry, unlike emissions from other agriculture in other Midwest states, which are dominated by N 2 O from corn production and crop/soil management (WRI, 2007). The State of Wisconsin has identified a number of regionally specific best management conservation practices and technical standards. In 1997 the Wisconsin Department of Agriculture, Trade, and Consumer Protection (DATCP) published a compilation of conservation practices to address manure storage, nutrient management, and other environmental issues. More recently, Wisconsin s Strategy for Reducing Global Warming (WI Global Warming Task Force, 2008) includes proposals to: Increase the capture and use of animal methane for electricity and/or heat; reduce current methane emissions from animals; Reduce the application of nitrogen and the overall use of chemical fertilizers; Implement best management practices for manure and nutrient management; and Increase the availability and use of renewable biomass and bio-fuels for electricity, heat, and transportation. Integration of dairy & bio-fuels in Wisconsin Typical dairy diets in Wisconsin are comprised of a combination of corn silage, alfalfa silage, corn grain, cotton seed, soybean meal (SBM) a co-product from soy oil production and, more recently, another valuable supplement: dry distillers grains with solubles (DDGS) a co-product of the corn ethanol industry. The sustainability of bio-energy feedstock supply depends on mutually beneficial integration with existing agricultural and forestry industries. The composition of the dairy diet plays an important role in GHG emissions not only by affecting enteric emissions from cows (direct effect) and changing the quantities or types of crops grown (indirect effect), but often times by interacting with bio-fuels production (synergistic effect). The bio-fuels industry in Wisconsin is comprised mainly of corn ethanol production with an installed capacity of 1.9 billion liters of ethanol (and more than 1 billion kg of DDGS) per year. From the perspective of Wisconsin s most important agricultural activity, dairy production, the corn ethanol industry can be seen as a feed pre-processing operation that produces DDGS to feed dairy cows, with ethanol as a co-product. 4

10 LIFE CYCLE ASSESSMENT (LCA) Land use, energy use and global warming potential can be assessed by using life cycle assessment (LCA) methods. LCA is: THE COMPILATION AND EVALUATION OF THE INPUTS, OUTPUTS AND THE POTENTIAL ENVIRONMENTAL IMPACTS OF A PRODUCT SYSTEM THROUGHOUTT ITS LIFE CYCLE, FROM RAW MATERIAL ACQUISITION THROUGH PRODUCTION, USE, END-OF-LIFE TREATMENT, RECYCLING AND FINAL DISPOSA AL (ISO, 2006A). LCA uses a product-oriented approach considering the whole life cycle of a specific product. LCA uses a structured and comprehensive method to evaluate the sustainability of production procedures (Figure 4). LCA quantifies all relevant emissions and resources consumed as well as environmental and health impacts that are associated with the entire life cycle of any goods and services ( European Union, 2010). LCA is used as a powerful decision support tool, complementing other methods, to identify and implement effective and efficient methods to make production more sustainable. LCA uses a rigorous scientific approach to quantify the effects of environmenta al policies and business decisions to achieve more sustainable production and consumer choices. The Integrated Product Policy (IPP) of the European Union states: ALL PRODUCTS CAUSE ENVIRONMENTAL DEGRADATION IN SOME WAY, WHETHER FROM THEIR MANUFACTURING, USE OR DISPOSAL. IPP SEEKS TO MINIMIZE THESE BY LOOKING AT ALL PHASES OF A PRODUCTS LIFE CYCLE AND TAKING ACTION WHERE IT IS MOST EFFECTIVE. LCA provides an excellent opportunity to avoid creating new problems while solving old ones. FIGURE 4. LCA STAGES (ISO 14040). The international standardd ISO series (listed below) present standardized methods for conducting LCAs ( iso.org/iso/home.htm) : Principles and framework 14041: Goal, scope and inventory analysiss 14042: Impact assessment 14043: Life cycle interpretation 14044: Requirements and guidelines 14047: Examples of application of ISO

11 14048: Data documentation format 14049: Examples of application of ISO to goal and scope definition and inventory analysis LCA terms and definitions Allocation: partitioning the input or output flows of a process between the primary product being studied and co-products resulting from the process. Functional unit: A specified quantity of the primary product being studied. Impact categories: Classes representing environmental issues of concern to which life cycle inventory analysis results may be assigned (e.g. global warming, depletion of abiotic resources (ADP), land use, eutrophication (EP), acidification (AP), photo-oxidant formation (POCP), stratospheric ozone depletion (ODP)) Input: product, material or energy flow that enters a unit process Life cycle assessment (LCA): compilation and evaluation of the inputs, outputs and the potential environmental impacts of a product system throughout its life cycle Life cycle inventory analysis (LCI): phase of LCA involving the compilation and quantification of inputs and outputs for a product throughout its life cycle Life cycle impact assessment (LCIA): phase of LCA aimed at understanding and evaluating the magnitude and significance of the potential environmental impacts for a product system throughout the life cycle of the product Life cycle interpretation: phase of LCA in which the findings of either the inventory analysis or the impact assessment, or both, are evaluated in relation to the defined goal and scope in order to reach conclusions and recommendations Output: product, material or energy flow that leaves a unit process System boundary: set of criteria which unit processes are part of a product system. 6

12 THE GREEN CHEESE PROJECT The Green Cheese model is a partial LCA of integrated dairy and bio-fuels production systems. This project idea grew out of discussions between: Progressive Dairy Producers; Who understand the need to prepare for carbon trading and other opportunities created by increased concerns about energy security and the environmental consequencess of energy use, The Wisconsin department of Agriculture, Trade and Consumer Protection, and The Wisconsin Department of Natural Resources; The state agencies that will provide regulatory and/or assistance programs for dairy farms moving toward more sustainable production practices, and Faculty at the UW college of Agricultural and Life sciences; Engaged in research, teaching and outreach activities related to sustainable dairy production systems. All of these organizations have provided input into the design of the project and the need for and utility of the tools to be developed. Green Cheese Objectives The objective of the Green Cheese project is to develop a tool that will provide guidance to dairy farmers, dairy processors and policy makers to: 1) Quantify and evaluate the energy, GHG and nutrient balances of dairy systems combined with bio- of fuel production, energy generation and conservation technologies; and 2) Investigate synergies and opportunities to reduce net energy intensity and environmental impact dairy and bio-fuel production in Wisconsin. Figure 5 shows the main processes within the life cycle of one kg of Cheddar cheese and the impact categories that are considered in this study. FIGURE 5. THE MAIN PROCESSES OF THE PRODUCTION OF CHEDDAR CHEESE AND THE RELATED IMPACT CATEGORIES. 7

13 Green Cheese Methods This study develops a partial LCA of milk and cheddar cheese production applying a system expansion approach to account for the interactions between the dairy and bio-fuels sectors in the state of Wisconsin. This is a partial LCA because: a) It does not assess environmental impacts of milk production in all impact categories, and b) It does not assess the impacts up to the end of life of the product (consumption and disposal). The cheese production system boundaries were expanded to include bio-fuels production with ethanol and bio-diesel accounted for as co-products. Total bio-fuel production was scaled to provide the amount of DDGS and SBM used to feed the dairy herd. We assumed that the production of ethanol and biodiesel would displace the production of gasoline and petro-diesel, respectively. The GHG that would otherwise have been emitted by the production and use of the displaced fuels (gasoline and petro-diesel) with the same energy content (in MJ) of the bio-fuels that were yielded were credited to the bio-fuels (corn ethanol and soybean diesel). The energy that would otherwise have been used in the production of the displaced fuels (gasoline and petro-diesel) with the same energy content (in MJ) of the bio-fuels that were yielded was credited to the bio-fuels (corn ethanol and soybean diesel). Nutrients application was based on the minimum requirement for each crop with crop yields reflecting historical Wisconsin averages. Synthetic fertilizers in the forms of N, P, and K were applied only to meet crop nutrient requirements not met with manure. Life Cycle Inventory Data The major components of our system model are: 1. Milk production: including dairy herd structure and animal nutrition; 2. Manure handling and storage: including biogas generation and field application of manure; 3. Crop production for dairy feeds and ethanol and biodiesel feedstock production; 4. Corn/ethanol and soybean/biodiesel conversion; and 5. Milk transportation from farm to plant, and cheese and whey processing. The life cycle inventory data were obtained from databases accessed through GaBI 4 Professional and other research literature where available and by our own calculations when Wisconsin-specific LCI data were not available. Impact Assessment The impact of Wisconsin dairy farming and cheese processing procedures on global warming potential and resource use are assessed including the following assumptions (Table 1): 8

14 TABLE 1. IMPACT CATEGORIES, INDICATORS AND CHARACTERIZATION FACTORS. Midpoint Impact Categories Inventory Parameters / Indicators Characterization factors (a) Unit Depletion of abiotic resources (ADP) Global warming potential (GWP) Net Energy intensity MJ Land use m 2 Carbon dioxide (CO 2 ) 1 kg CO 2 -eq Nitrous oxide (N 2 O) 298 kg CO 2 -eq Methane (CH 4 ) 25 kg CO 2 -eq (a) Characterization factors of GWP for a 100-year time horizon (Forster et al., 2007) Net energy intensity was defined as the net energy from activities related to milk and bio-fuel production, calculated as the difference between the energy inputs (required energy) and energy outputs (supplied energy), and discounting the avoided energy use, as shown in the equation below. Net energy intensity (MJ/kg ECM) = [ (E I ) (E O ) (E A )] / kg ECM Where: E I (MJ) = energy inputs to the system, including on-farm and off-farm inputs for crops production and for bio-fuels production E O (MJ) = energy generated in form of bio-fuel or biogas E A (MJ) = avoided energy use due to displacement of other fuels production Milk Production at the Farm-Gate The boundaries of the farm system were milk production from cradle to farm gate in Wisconsin (Figure 6). Included in the boundaries are: crops production for dairy feed, for corn ethanol, and for soy biodiesel production, off-farm production of nutrient and energy inputs for crops, and the corn to ethanol and the soybean to biodiesel conversion process. The characteristics of the herd archetype used in this study are listed in Table 2. The functional unit for this part of the system was 1 kg of energy corrected milk (ECM) to 4.0% fat and 3.3% protein. We estimated the effects of five different dairy diets characterized by different forage types (corn silage and alfalfa) and different amounts of soybean meal (SBM) and dried distiller grains with soluble (DDGS) (Table 3). We also explored two manure management practices; with and without anaerobic digesters. In the biogas scenarios it was assumed that the displaced fossil fuel would be natural gas because of its similarity to biogas, and because it can be used for either heat or (electric) power generation. GHG credits for avoided natural gas production and combustion were calculated as the GHGs that would be emitted by the production and combustion of the amount of natural gas with the same energy content (MJ) as the biogas. Meat (from culled animals) that was suitable for human consumption was accounted for as a co-product from milk production, and was valued based on the nutritional content (protein and fat) in boneless meat produced 9

15 compared to the nutritional value of milk produced during the same time period. This approach resulted in: 98.99% of the system inputs and outputs being attributed to milk, and 1.01% to meat. TABLE 2. INPUTS FOR MILK PRODUCTION AND DAIRY HERD STRUCTURE. Inputs Values used in this study Desired milk production 10,000 kg/day Milk protein 3.1% Milk fat 3.7% Milk lactose 4.85% Body weight of non-pregnant adult dairy cows 650 kg Daily milk production per cow 35 kg Dry period 62 days (AgSource, 2009) Calving interval 14 months (AgSource, 2009) Annual adult replacement rate % (AgSource, 2009) Annual mortality rate for weaned heifers 1.8% (USDA, 2007) Annual mortality rate for unweaned heifers 7.8% (USDA, 2007) Abortions neglected New born female:male ratio (Del Rio et al., 2007) Milk intake by calves up to 30 days old 4 kg milk per calf per day Electricity for housing and milking MJ/kg milk (ECW, 2005) TABLE 3. DAIRY DIETS IN THE GREEN CHEESE MODEL. Corn silage Alfalfa silage Dairy percentage in dry percentage in dry diets matter intake (DMI) matter intake (DMI) CADS 29% 29% Levels of concentrates DDGS and Soybean meal providing equal amounts of protein CSDG 36% 22% Maximizing DDGS CSSB 36% 22% Maximizing Soybean meal ASDG 22% 36% Maximizing DDGS ASSB 22% 36% Maximizing. Soybean meal 1 Includes mortality and culling. 2 Includes energy for space heating, ventilation, lighting, milking, milk cooling, and water heating. 10

16 FIGURE 6. System boundarries of the milk production phase. FIGURE 7. System S bound daries of the dairy d plant phhase. 11

17 Milk Processing and Cheese-making The final functional unit of this study is 1 kg Cheddar cheese produced in Wisconsin. The processing calculations were done from farm gate to dairy plant gate. The processing system boundaries include the transportationn of milk from the farm to the dairy plant and the processing at the dairy plant (Figure 7). Two scenarios were modeled for a medium scale plant in Wisconsin: Scenario 1: Production of cheddar cheese as the only product. Sweet whey is sold to aggregate processors or is land-spread. Scenario 2: Production of cheddar cheese as the main product, and dry whey and whey cream as co-products. Since more than one valuable product is produced at the dairy plant, allocation decisions based on physical processes and total solids were made to distribute the environmental impacts of producing one kilogram of cheddar cheese (Figure 8) ). In scenario 1, energy consumed and greenhouse gas emissions were all assigned to the cheese as it is the only valuable product. In scenario 2, the environmental impacts were allocated among the cheddar cheese, the dry whey, and the whey cream. A physical allocation was done according to the energy consumption related to each product: Processes that exist only for the cheese production: packaging of cheese. Processes that exist only for the whey production: pasteurization of clarified whey, reverse osmosis, evaporation, drying, and packaging of whey. Processes that exist only for the whey cream production: separation of whey cream. An allocation based on total solids was done for the common processes to these three products: transportation of milk, reception, pasteurization, making of vats, cleaning, lighting, and mechanical power processes. FIGURE 8. ALLOCATION BASED ON PHYSICAL PROCESSES AND TOTAL SOLIDS IN CHEESE PRODUCTION 12

18 RESULTS AND INTERPRETATION Milk Production Net energy intensity, GHGG emissions and Land use of selected milk production systems in Wisconsin were estimated. Results were compared within five scenarios using diets supplemented with differing amounts of DDGS and SBM and with two different manure management practices: with and without on-farm biogas generation. Net Energy Intensity The net energy intensity of milk production for the 5 diary diets are presented in Figure 9. The first column for each diet applies no credits for energy produced in the milk production system. The second column for each diet includes energy credits for the production of bio-fuels. The third column for each diet includes energy credits for biogas and biofuels production. The net energy inputs for the diet maximizing DDGS feeding were about 20% higher than for the other diets but when accounting for the energy credits for ethanol this dies had the lowest net energy intensity. The energy implications of feeding soy bean meal weree much smaller than for feeding DDGS. Likewise the energy implications of the type of forage used were small. FIGURE 9. NET ENERGY INTENSITY OF MILK PRODUCTION FOR SELECTED DIETS, WITH DIFFERENT ACCOUNTING CRITERIA. NEGATIVE VALUES OF NET ENERGY INTENSITY INDICATE NET POSITIVE ENERGY OUTPUT FROM THE SYSTEM ACCOUNTING FOR THE ENERGY CONTENT OF THE BIO-FUELS PRODUCED OR FOR THE AVOIDED ENERGY TO PRODUCE FOSSIL FUELS. 13

19 Energy production from systems that account for biofuels production and biogas production help reduce net energy intensity of milk production (Figure 10). FIGURE 10. DIRECT ENERGY IS THE ENERGY USED ON THE FARM IN FORMS OF ELECTRICITY AND FUELS. INDIRECT ENERGY IS THE ENERGY USED TO PRODUCE THE FERTILIZERS, SEEDS, HERBICIDES, PESTICIDES, LIME, LIQUID FUELS, ELECTRICITY, NATURAL GAS, AND MACHINERY USED FOR FARMING. GHG Emissions Our results account for the emissions related to the production of enough corn and soybeans to generate the DDGS and SBM in the diets. The largest single contributor to GHG emissions in milk production up to the farm gate was enteric CH4 emissions (52% of total GHGs from milk production), ranging from 0.42 to 0.44 kg CO2-eq/kg ECM. The difference between the scenarios (6.6% from the lowest to the highest value) was due to the difference in the diet compositions of the lactating herd. This emphasizes the need for diets that might result in less CH4 emissions, and the development of more accurate methods to estimate those emissions. The average GHG emissions from milk production in the scenarios that did not include bio-fuels production ranged from 0.80 to 0.89 kg CO2-eq/kg ECM. The results were quite different when the system boundaries of the LCA weree expanded to include bio-fuels production. Diets high in corn silage and DDGS had the lowest GHG emissions (Diet CSDG: 0.66 kg CO2- eq/kg ECM), and diets with more alfalfa silage and no DDGS had the greatest emissions (Diet ASSB: 0.78 kg CO2-eq/kg ECM). The average for all scenarios was 0.74 kg CO2-eq/kg ECM accounting for bio-fuels, or 90% of the original value, when bio-fuels production was not considered. The differencee in GHG emissions was mainly due to the avoidance of fossil fuels production and combustion. 14

20 FIGURE 11. COMPARISON AMONG FIVE DAIRY DIETS IN BEST MANAGEMENT PRACTICES (IN THE GREEN CHEESE MODEL) AND THE DMI STUDY ON REGION 3 (WHICHH INCLUDES WISCONSIN) SHOWS THAT THE 2 MAJOR AREAS IN WHICH THERE IS ROOM FOR IMPROVEMENT ARE: MANURE MANAGEMENT AND CROP PRODUCTION SYSTEMS. The major differences in GHG emissions between the scenarios assessed in the Green Cheese study and the DMI study results for Region 3 (which includes Wisconsin) (see Figure 11) are due to differences in emissions from both manure management and crop production sectors. In the Green Cheese study the scenarios were based on best management practices, while the DMI study used statistical and survey data for its assessment. The Green Cheese estimates were within the distribution of farms surveyed for the DMI study. This indicates that there are farms in Wisconsin that are successfully using the best management practices assumed in the Green Cheesee study. Another implication of this result is that there are opportunities to reduce the environmental impact of dairy production in Wisconsin by wider adoption of best management practices for manure handling, crop production and feeding efficiency. The addition of anaerobic manure digestion resulted in total GHG emissions ranging from 0.43 to 0.55 kg CO2-eq/kg ECM (Figure 5) or 70-75% of the value that accounted for liquid bio-fuels alone. The further reduction in emissions was due mainly to the avoided natural gas production and combustion (0.18 kg CO2- eq/kg ECM), and secondarily to avoided CH4 emissions from manure storage (0.05 kg CO2-eq/kg ECM). The average effect of including anaerobic digesters for on-farm biogas generation reduced GHG emissions from milk production by 0.25 kg CO2-eq/kg ECM. If the biogas was used to generate electricity the avoided emissions for electricity production would be smaller (0.12 kg CO2-eq/kg ECM) than the avoided emissions for natural gas production and combustion (because Wisconsin s electricity matrix includes energy sources that emit less GHG/MJ than natural gas, such as wind and nuclear. The net GHG emissions for all scenarios are presented in Figure 12. When the system generated bio-fuels and biogas, less fossil fuels were used and overall GHG emissions were smaller. The least GHG emission resulted from scenarios that included DDGS in the diets and used anaerobic digesters. The reduction in 15

21 overall GHG emissions resulted from the avoidance of fossil fuels production and combustion when the system generates bio-fuels and biogas. The effect of the DDGS fraction in the diet can be assessed by comparing the first to the second bars for each scenario in Figure 12. Diets CSSB and ASSB had no DDGS in the lactating cows ration. The effect of biogas generation can be assessed by comparing the second to the third bars for each scenario in Figure 12. Diets CSDG and ASDG were high in DDGS but showed large differences in overall GHG emissions. These differences highlight the influence that the forage fraction of the diets could have on the final results. FIGURE 12 GHG EMISSIONS FROM MILK PRODUCTION FOR SELECTED DIETS, ACCORDING TO DISTINCTT ACCOUNTING CRITERIA. The effect of anaerobic digesters can be analyzed in two separate ways: 1. The direct benefit of simply capturing and flaring the biogas (transforming methane into carbon dioxide); 2. The indirect benefit of using the biogas to displace natural gas (thus avoiding the emissions related to natural gas production and combustion). Combustion of biogas per se reduces GHG emissions by around 6.6% to 7.1%. If biogas is used to replace natural gas, GHG emissions are reduced by 32% to 38%. The effect of the use of biogas on GHG emissions and net energy intensity of milk production: In the Green Cheesee study, the use of biogas from anaerobic digesters reflected in reductions of 30-35% in CO2-eq/kg ECM and % in MJ/kg ECM. 16

22 FIGURE 13 GHG EMISSIONS AND NET ENERGY INTENSITY OF MILK PRODUCTION UP TO FARM GATE. THE EFFECT OF ANAEROBIC DIGESTERS IS MILD WHEN BIOGAS IS NOT USED AS A FUEL REPLACING NATURAL GAS, AND LARGER WHEN IT IS USED AS A FUEL, ESPECIALLY IN TERMS OF NET ENERGY INTENSITY. NEGATIVE VALUES OF NET ENERGY INTENSITY INDICATE NET POSITIVE ENERGY OUTPUT FROM THE SYSTEM ACCOUNTING FOR THE ENERGY CONTENT OF THE BIO-FUELS PRODUCED OR FOR THE AVOIDED ENERGY TO PRODUCE FOSSIL FUELS. Land use The average land area needed to support the five production systems ranged from 1.68 m2/kg ECM to 2.00 m2/kg ECM (Figure 14). The diet thatt maximized DDGS feeding showed about 17% increase in land used compared to the other diets. The increment occurred because land was used to produce corn for the ethanol industry, from which DDGS are co-products. There was very little difference in land use for the acrosss the other diets. There was no excess manure for any of the scenarios, indicating that the land base used to grow the crops to supply these dairy rations was capable of sustainably absorbing all of the manure from the dairy herd. It is important to note that this assumes optimal efficiency in manure collection, application and nutrient management. Within diets with the same forage compositions, those with more DDGS than SBM had greater need for purchased N, because the corn crop required additional N fertilizer and soybeans did not. COMBINED ASPECTS In Figure 14, the results are presented in relation to scenario CADS, which results were reported as being 100%. When evaluating the three aspects (land, GHG, and energy) combined, without accounting for bio- fuels, scenarios with more DDGS (Diets CSDG and ASDG) used more land, emitted more GHG, and had higher net energy intensity per kg of ECM when compared to other diets within the same group in terms of forage. However, when accounting for bio-fuels production and the correspondent displacement of fossil fuels, scenarios with more DDGS (Diets CSDG and ASDG) emitted less GHG and had lower net energy intensity per 17

23 kg of ECM when compared to other diets within the same group in terms of forage (Diets CSSB and ASSB) ( Figure 14). Finally, when anaerobic digestion for manure treatment was implemented, the effects of biogas generation on GHG emissions and especially on net energy intensity were highly positive (fourth bar in Figure 14). FIGURE 14. LAND USE, GHG EMISSIONS, AND NET ENERGY INTENSITY OF MILK PRODUCTION FOR SELECTED DIETS, ACCOUNTING FOR BIO-FUELS. ALL VALUES PRESENTED IN RELATION TO DIET CADS (100%). THE TWO BARS AT THE RIGHT SHOW THE NET ENERGY INTENSITY WITHOUT AND WITH BIOGAS. NEGATIVE VALUES OF NET ENERGY INTENSITY INDICATE NET POSITIVE ENERGY OUTPUT FROM THE SYSTEM ACCOUNTING FOR THE ENERGY CONTENTT OF THE BIO-FUELS PRODUCED OR FOR THE AVOIDED ENERGY TO PRODUCE FOSSIL FUELS. 18

24 Results from the Dairy Plant phase For each kilogram of cheddar cheese, 0.61 kg of dry whey and 0.1 kg of whey cream are produced. Net energy intensity and GHG emissions of cheese production systems in Wisconsin were estimated. Results were compared within two scenarios: not producing and producing dry whey. The results for net energy intensity and GHG emissions are presented in the following sectors: transportation, cheese processing activities, and whey drying activities (when applied). Results were calculated per kg of cheddar cheese made with milk containing 3.7% fat and 3.1% protein, and using an allocation factor of 50.1% to the cheese, 47.3% to the dry whey, and 2.6% to the whey cream for the common processes, which were determined according to the total solids. The composition of the raw incoming milk and the final products is described in Table 4: TABLE 4. COMPOSITION OF PRODUCTS AND OUTCOMES IN CHEESE PRODUCTION. Composition of products and outcomes (% of raw incoming milk) Products Water Protein Fat Carbohydrates Ash Total Solids Incoming milk Cheese Whey cream Dried whey

25 Dairy Farm gate to Dairy Plant gate ENERGY INTENSITY Scenario 1: production or cheese only When considering cheddar cheese as the only output, 7.54 MJ are needed to produce one kilogram of cheese (Table 5). Of this energy, 9.4 % is used when transporting the milk from the farm to the dairy plant and 90.6% is used at the dairy plant when processing the cheese (Figure15). TABLE 4. ENERGY INTENSITY WHEN ONLY CHEESE IS PRODUCED. Energy MJ/kg cheese (scenario 1: production of cheese only) Transportation 0.71 Dairy plant (cheese only) 6.83 Total 7.54 FIGURE 15. ENERGY INTENSITY OF CHEESE PRODUCTION WHEN ONLY CHEESE IS PRODUCED. Even though electricity represents one third of the total energy consumption and thermal energy the rest two thirds when producing cheese only, the embedded energy that goes into electricity production makes it more than 60% when talking about net energy. 20

26 Scenario 2: production of cheese, dry whey, and whey cream When cheddar cheese, dry whey, and whey cream are the outcomes, a total of MJ are needed to produce one kilogram of cheese (Table 6 and Figure 16). The transportationn of the milk from the farm to the dairy plant epresent 4.5% %, cheese processing activities represent 43.5%, and whey processing activities represent the rest 52%. After allocating the total solids among the common processes for the cheese, dry whey, and whey cream, 3.96 MJ/kg cheese are assigned to the cheese, MJ/kg cheese to the dry whey, and 0.62 MJ/kg cheese to the whey cream. TABLE 5. ENERGY INTENSITY OF CHEESE PRODUCTION WHEN CHEESE, DRY WHEY, AND WHEY CREAM ARE PRODUCED. Energy MJ/kg cheese (scenario 2: production of cheese, dry whey and whey cream) Products Transportation Cheese processing Whey processing Total Cheese Dry Whey Whey Cream Total FIGURE 16. ENERGY INTENSITY OF CHEESE PRODUCTION WHEN CHEESE, DRY WHEY, AND WHEY CREAM ARE PRODUCED. Electricity represents nearly 20% of the total energy consumption and thermal energy the remaining 80% when considering scenario 2; however, the embedded energy that goes into electricity production makes it nearly 40% of the total net energy. 21

27 FIGURE 17. COMPARISON OF ENERGY INTENSITY OF SCENARIO 1 (ONLY CHEESE IS PRODUCED) TO SCENARIO 2 (CHEESE AND WHEY ARE PRODUCED) GHG EMISSIONS Scenario 1: production of cheese only GHG emissions result mainly from the combustion of the fuels consumed at the dairy plant in the forms of natural gas and electricity. Total GHGG emissions from scenario 1 are 0.51 kg of CO2-eq/kg of cheese (Table 7 and Figure 18). Of these emissions, 90.2% occurs at the dairy plant and 0.8% occurs when transporting the milk from the farm to the dairy plant. TABLE 6. GREENHOUSE GAS EMISSIONS WHEN ONLY CHEESE IS PRODUCED. GHG emissions kg CO 2 2-eq/kg cheese (scenario 1: production of cheese only) Transportation Dairy plant (cheese only) Total GHG emissions CO2-eq/ kg cheese (scenario 1: production of cheese only) 0.05 Transportation 0.46 Dairy plant (cheese only) FIGURE 18. GHG EMISSIONS WHEN ONLY CHEESE IS PRODUCED. 22

28 As the electricity matrix in Wisconsin (and the U.S. in general) has coal as the major source, the emissions per MJ of electricc energy required are higher than those related with thermal energy requirements that are accomplished with natural gas. Scenario 2: production of cheese, dry whey, and whey cream When modeling scenario 2, total emissions are 1.06 kg of CO 2 -eq/kg of cheese (Table 8 and Figure 19). Of these emissions, 4.5% happen when transporting the milk, 43.5% from the cheese processing activities, and 52% from the whey processing activities. TABLE 7. GREENHOUSE GAS EMISSIONS WHEN CHEESE, DRY WHEY, AND WHEY CREAM ARE PRODUCED. GHG emissions kg CO 2 -eq/kg cheese (scenario 2: production of cheese, dry whey, and whey cream) Products Transportation Cheese processing Whey processing Total Cheese Dried Whey Whey Cream Total GHG emissions CO2-eq/ kg cheese (scenario 2: production of cheese, dry whey and whey cream) Transportation Cheese processing Whey processing FIGURE 19 GHG EMISSIONS WHEN CHEESE, DRY WHEY, AND WHEY CREAM ARE PRODUCED.. After allocating total solids among common processes for the main product and co-products 0.27 kg CO2- eq/kg cheesee are assigned to the cheese, 0.75 kg CO 2 -eq/kg cheese to the dry whey, and 0.04 kg CO2- eq/kg cheesee to the whey cream. 23

29 Scenario 2 assigns less energy consumption and GHG emissions to cheese because there are other valuable products that share the burden of the common processes, contrary to scenario 1 where all environmental impacts are assigned to cheese. Drying the whey is a very energy intensive process and thus, this activity captures 71% of the total emissions of the dairy plant modeled in scenario 2 (Figure 20) ). Dry whey requires most of the energy and emits most GHG emissions when compared to the main product cheese despite the fact that it is a co-product with less market value. FIGURE 20 COMPARISON OF GHG EMISSIONS FOR SCENARIO 1 (ONLY CHEESE IS PRODUCED) AND SCENARIO 2 (CHEESE AND WHEY ARE PRODUCED). Cradle to Dairy Plant gate To calculate the aggregated energy intensity and GHG emissions for one kilogram of cheese, an average for the five diets described before was taken. Milk yield and the scenarios that accounted for biofuels and biogas were considered in the dairy farm and aggregated to the two scenarios modeledd in the dairy plant s module. The results for energy intensity and GHG emissions per kilogram of cheddar cheese are presented below for each scenario. 24

30 ENERGY INTENSITY Scenario 1: production of cheese only TABLE 8. SCENARIO 1. NET ENERGY INTENSITY WHEN ONLY CHEESE IS PRODUCED. AGGREGATED VALUES OF BOTH MILK PRODUCTION AND CHEESE PROCESSING PHASES. Energy intensity (MJ/kg cheese) Milk yield 65 Milk yield 70 Milk yield 77.2 Without biodigesters Not accounting for biofuels Accounting for biofuels Not accounting for biofuels, not using biogas With biodigesters Accounting for biofuels, not using biogas Accounting for biofuels, using biogas Scenario 2: production of cheese, dry whey, and whey cream Energy intensity for cheese. TABLE 9. SCENARIO 2. NET ENERGY INTENSITY OF CHEESE PRODUCTION WHEN CHEESE, DRY WHEY, AND WHEY CREAM ARE PRODUCED. AGGREGATED VALUES OF BOTH MILK PRODUCTION AND CHEESE PROCESSING PHASES Energy intensity (MJ/kg cheese) Milk yield 65 Milk yield 70 Milk yield 77.2 Without biodigesters Not accounting for biofuels Accounting for biofuels Not accounting for biofuels, not using biogas With biodigesters Accounting for biofuels, not using biogas Accounting for biofuels, using biogas

31 Energy Intensity for dry whey TABLE 10. SCENARIO 2. NET ENERGY INTENSITY OF DRY WHEY WHEN CHEESE, DRY WHEY, AND WHEY CREAM ARE PRODUCED. AGGREGATED VALUES OF BOTH MILK PRODUCTION AND CHEESE PROCESSING PHASES. Energy intensity (MJ/kg cheese) Milk yield 65 Milk yield 70 Milk yield 77.2 Without biodigesters Not accounting for biofuels Accounting for biofuels Not accounting for biofuels, not using biogas With biodigesters Accounting for biofuels, not using biogas Accounting for biofuels, using biogas Energy Intensity for whey cream TABLE 11. SCENARIO 2. NET ENERGY INTENSITY FOR WHEY CREAM PRODUCTION WHEN CHEESE, DRY WHEY, AND WHEY CREAM ARE PRODUCED. AGGREGATED VALUES OF BOTH MILK PRODUCTION AND CHEESE PROCESSING PHASES Energy intensity (MJ/kg cheese) Milk yield 65 Milk yield 70 Milk yield 77.2 Without biodigesters Not accounting for biofuels Accounting for biofuels Not accounting for biofuels, not using biogas With biodigesters Accounting for biofuels, not using biogas Accounting for biofuels, using biogas

32 GHG emissions Scenario 1: production of cheese only TABLE 12. SCENARIO 1. GREENHOUSE GAS EMISSIONS FROM CHEESE PRODUCTION WHEN ONLY CHEESE IS PRODUCED. AGGREGATED VALUES OF BOTH MILK PRODUCTION AND CHEESE PROCESSING PHASES GHG (kg CO2-eq/kg cheese) Milk yield 65 Milk yield 70 Milk yield 77.2 Without biodigesters Not accounting for biofuels Accounting for biofuels Not accounting for biofuels, not using biogas With biodigesters Accounting for biofuels, not using biogas Accounting for biofuels, using biogas Scenario 2: production of cheese, dry whey, and whey cream GHG emissions for cheese TABLE 13. SCENARIO 2. GREENHOUSE GAS EMISSIONS FROM CHEESE PRODUCTION WHEN CHEESE, DRY WHEY, AND WHEY CREAM ARE PRODUCED. AGGREGATED VALUES OF BOTH MILK PRODUCTION AND CHEESE PROCESSING PHASES. GHG (kg CO2-eq/kg cheese) Milk yield 65 Milk yield 70 Milk yield 77.2 Without biodigesters Not accounting for biofuels Accounting for biofuels Not accounting for biofuels, not using biogas With biodigesters Accounting for biofuels, not using biogas Accounting for biofuels, using biogas

33 GHG emissions for dry whey TABLE 14. SCENARIO 2. GREENHOUSE GAS EMISSIONS DUE TO DRY WHEY PRODUCTION WHEN CHEESE, DRY WHEY, AND WHEY CREAM ARE PRODUCED. AGGREGATED VALUES OF BOTH MILK PRODUCTION AND CHEESE PROCESSING PHASES. GHG (kg CO2-eq/kg cheese) Milk yield 65 Milk yield 70 Milk yield 77.2 Without biodigesters Not accounting for biofuels Accounting for biofuels Not accounting for biofuels, not using biogas With biodigesters Accounting for biofuels, not using biogas Accounting for biofuels, using biogas GHG emissions for whey cream TABLE 15. SCENARIO 2. GREENHOUSE GAS EMISSIONS DUE TO WHEY CREAM PRODUCTION WHEN CHEESE, DRY WHEY, AND WHEY CREAM ARE PRODUCED. AGGREGATED VALUES OF BOTH MILK PRODUCTION AND CHEESE PROCESSING PHASES. GHG (kg CO2-eq/kg cheese) Milk yield 65 Milk yield 70 Milk yield 77.2 Without biodigesters Not accounting for biofuels Accounting for biofuels Not accounting for biofuels, not using biogas With biodigesters Accounting for biofuels, not using biogas Accounting for biofuels, using biogas

34 CALCULATIONS FOR THE STATE OF WISCONSIN From cradle to farm gate If we were to consider the total annual milk production in Wisconsin of 25,239 million lb. in 2010 (USDA/NASS, 2010), we can estimate the total net energy and GHG emissions due to milk production for the whole state. Because the maximization of DDGS in dairy diets and the use of anaerobic digesters to generate biogas from manure were the most significant factors influencing the net energy intensity and GHG emissions per unit of milk produced, the following scenarios were modeled for the state s milk production regarding those factors: 1) 0% of milk produced with maximized DDGS in dairy diets, 0% of manure in anaerobic digesters; 2) 0% of milk produced with maximized DDGS in dairy diets, 50% of manure in anaerobic digesters; 3) 0% of milk produced with maximized DDGS in dairy diets, 100% of manure in anaerobic digesters; 4) 50% of milk produced with maximized DDGS in dairy diets, 0% of manure in anaerobic digesters; 5) 50% of milk produced with maximized DDGS in dairy diets, 50% of manure in anaerobic digesters; 6) 50% of milk produced with maximized DDGS in dairy diets, 100% of manure in anaerobic digesters; 7) 100% of milk produced with maximized DDGS in dairy diets, 0% of manure in anaerobic digesters; 8) 100% of milk produced with maximized DDGS in dairy diets, 50% of manure in anaerobic digesters; 9) 100% of milk produced with maximized DDGS in dairy diets, 100% of manure in anaerobic digesters. TABLE 16. ESTIMATED GREENHOUSE GAS EMISSIONS DUE TO ANNUAL MILK PRODUCTION IN WISCONSIN. SELECTED SCENARIOS VARY IN PERCENTAGE OF ADOPTION OF TWO PRACTICES: MAXIMIZATION OF DDGS INCLUSION IN DAIRY DIETS, AND USE OF ANAEROBIC DIGESTION OF DAIRY MANURE TO GENERATE BIOGAS WHICH WILL REPLACE NATURAL GAS. GHG emissions due to Milk Production in Wisconsin (million Ton CO 2 eq) Use of anaerobic digestion of dairy manure to generate biogas which will replace natural gas (in % of manure produced) Maximization of DDGS inclusion in dairy diets (in % of milk produced) 0% 50% 100% 0% % %

35 TABLE 17. ESTIMATED NET ENERGY INTENSITY OF ANNUAL MILK PRODUCTION IN WISCONSIN. SELECTED SCENARIOS VARY IN PERCENTAGE OF ADOPTION OF TWO PRACTICES: MAXIMIZATION OF DDGS INCLUSION IN DAIRY DIETS, AND USE OF ANAEROBIC DIGESTION OF DAIRY MANURE TO GENERATE BIOGAS WHICH WILL REPLACE NATURAL GAS. NEGATIVE VALUES MEAN THAT ENERGY PRODUCTION WAS LARGER THAN CONSUMPTION. Net Energy intensity of Milk Production in Wisconsin (million GJ) Use of anaerobic digestion of dairy manure to generate biogas which will replace natural gas (in % of manure produced) Inclusion of maximized DDGS in dairy diets (in % of milk produced) 0% 50% 100% 0% % (0.91) (3.95) (6.98) 100% (16.82) (19.86) (22.89) TABLE 18. ESTIMATED ENERGY PRODUCTION FOR ANNUAL MILK PRODUCTION IN WISCONSIN. SELECTED SCENARIOS VARY IN PERCENTAGE OF ADOPTION OF TWO PRACTICES: MAXIMIZATION OF DDGS INCLUSION IN DAIRY DIETS, AND USE OF ANAEROBIC DIGESTION OF DAIRY MANURE TO GENERATE BIOGAS WHICH WILL REPLACE NATURAL GAS. NEGATIVE VALUES MEAN ENERGY PRODUCTION. Energy Production from Dairy Systems (million GJ) Use of anaerobic digestion of dairy manure to generate biogas which will replace natural gas (in % of manure produced) Inclusion of maximized DDGS in dairy diets (in % of milk produced) 0% 50% 100% 0% 0 (2.06) (4,11) 50% (14.38) (16.40) (18.43) 100% (28.76) (30.75) (32.74) From farm gate to plant gate If we consider the last available Wisconsin cheese statistics from USDA, the production of cheese (excluding cottage cheese) in Wisconsin was 2,629,563 thousand pounds (1,192,762 ton) in Assuming that all cheese varieties have similar energy requirements and similar emissions to cheddar cheese, total net energy and GHG emissions of cheese production can be estimated for the state of Wisconsin. Cheese and whey are the main focus of this study; therefore, three general scenarios were modeled for the state s cheese production: 1) 0% of the cheese production considered whey drying; 2) 50% of the cheese production considered whey drying; and 3) 100% of the cheese production considered whey drying, as presented in Table

36 TABLE 19. ESTIMATED NET ENERGY INTENSITY OF ANNUAL CHEESE PRODUCTION IN WISCONSIN. Net Energy Intensity of Cheese Production in Wisconsin (million GJ) Whey Drying Scenarios Product 0% 50% 100% Cheese Whey Whey Cream TOTAL FIGURE 21. NET ENERGY OF AGGREGATED ANNUAL CHEESE PRODUCTION IN WISCONSIN, FOR SELECTED SCENARIOS Total net energy is higher when producing dry whey as a co-product than when producing cheese as the only product; however, as more whey is dried in the state, less energy is attributed to cheese (Figure 21). The reduction in net energy is explained by the high energy use of the whey drying process. Since drying whey requires so much energy, the allocation strategy (explained in the methods section) assigns more energy to this co-product; thus, contrary to the cheese, as more dry whey is produced in the state, more energy is equired by this co-product. 31

37 As in net energy consumption, as more dried whey is produced in the state, less GHG emissions are attributed to the cheese and more to the dry whey (Table 21 and Figure 22). Whey cream will follow the same tendency as dry whey, but it represents less than 4% of total emissions. TABLE 20. ESTIMATED GREENHOUSE GAS EMISSIONS FROM ANNUAL CHEESE PRODUCTION IN WISCONSIN. GHG emissions from Cheese Production in Wisconsin (thousand Ton CO 2 eq) Product Whey Drying Scenarios 0% 50% 100% Cheese Whey Whey Cream TOTAL ,263 GHG emisions (kg CO2-eq) GHG Emissions from Cheese Production in Wisconsin (kg CO 2 -eq) 1.0E E E E E E E E E E E+00 Cheese Whey Whey Cream Whey drying 0% Whey drying 50% Whey drying 100% FIGURE 22. GHG EMISSIONS FROM AGGREGATED ANNUAL CHEESE PRODUCTION IN WISCONSIN, FOR SELECTED SCENARIOS. 32

38 PRACTICES TO REDUCE ENVIRONMENTAL IMPACTS OF DAIRY PRODUCTION Co-products from corn ethanol production (dry distillers grains with solubles DDGS) Including DDGS in dairy diets results in decreased GHG emissions and net energy intensity per unit of milk produced (due to credits related to ethanol use). However, the inclusion of DDGS in dairy diets also implies that more land is being devoted for corn ethanol production, and thus resultss in more GHG emissions and energy use to produce that corn. Milk yield One of the major factors influencing both GHG emissions and energy intensity on dairy farms is the milk yield per cow. FIGURE 23 EFFECT OF MILK YIELD ON THE ENERGY INTENSITY AND GHG EMISSIONS FROM MILK PRODUCTION. In general, the highest the milk yield per cow, the lowest impact per unit of milk producedd on both GHG emissions and energy intensity (Figure 23). Manure management Manure is one of the most important waste streams that need to be handled in dairy farms. However, manure s nitrogen, phosphorus, and potassium contents make it an attractive substitute of synthetic fertilizers that require high fossil fuel energy inputs. Efficiency in converting manure from a waste stream to a valuable product through its utilization as fertilizer is one of the best management practices that can help reduce both GHG emissions and energy use. Manure exposure to moisture and highh temperatures increase the potential of GHG emissions mainly in the forms of nitrous oxide and carbon dioxide in aerobic conditions, and methane in anaerobic conditions. 33

39 Therefore, reducing the time exposure of manure to these factors (from collection to application) by using frequent haul systems, also result in a reduction of GHG emissions. In Wisconsin, frequent manure application to fields is not possible during winter, but if total solids content in manure is relatively high (more than 10% solids) manure can be stored in piles, where emissions won t be as high as if it was mixed with water and stored in pounds. However, when total solids in manure are less than 10%, a storage system such as a pond or a lagoon is needed. In these systems, emissions are directly related to the storage time and temperature, summer being the most critical period. Besides minimizing storage time, one strategy to reduce emissions is to minimize the area of exposure in manure ponds. To achieve this goal, one practice is to reduce the amount of water added to the manure, which means less volume and thus less handling costs. Covering the manure storage ponds with a synthetic material could also help to reduce GHG emissions. Even though this cover will create an anaerobic environment where methane will be formed, the capturing of this gas and further flaring will reduce net GHG emissions as methane will be combusted into carbon dioxide. This covering will also reduce nitrous oxide and carbon dioxide emissions, odor, and rain water entering the ponds. Manure can be applied by surface spreading or by injection. Injection of manure into the soil is the recommended practice as it reduces the volatilization of both methane and nitrous oxide. Anaerobic digesters Besides the adoption of best management practices for manure management, one manure treatment that can significantly influence on-farm GHG emissions is its anaerobic digestion followed by capture of the biogas. In confined herds where liquid manure is stored in ponds/lagoons, anaerobic digesters also improve nutrient and manure management, reduce odor, and decrease the population of weed seeds and pathogens in manure. The combustion of CH 4 that would otherwise be emitted from liquid manure stored in ponds/lagoons reduces GHG emissions by converting CH 4 into a less potent GHG (CO 2 ). FIGURE 24 ANAEROBIC DIGESTER - CRAVE BROTHERS FARM, WATERLOO, WISCONSIN. The liquid part of manure (digested or not) is rich in Nitrogen, which can be used as fertilizer for crop production. After anaerobic digestion of manure, digested solids can be utilized as compost (rich in Phosphorus) or animal bedding. 34